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OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
On October 25, 2019, Google announced that they had started applying BERT models for English language search queries within the US. [27] On December 9, 2019, it was reported that BERT had been adopted by Google Search for over 70 languages. [28] [29] In October 2020, almost every single English-based query was processed by a BERT model. [30]
The SDMX converter is an open source application that offers the ability to convert DSPL (Google's Dataset Publishing Language) messages to SDMX-ML, and vice versa. The output file of a DSPL dataset is a zip file containing data (in the form of CSV files) and metadata (as an XML file). Datasets in this format can be visualized in the Google ...
Pages in category "Datasets in machine learning" The following 12 pages are in this category, out of 12 total. ... Training, validation, and test data sets
Google Assistant: is a virtual assistant software application since 2023 developed by Google AI. Serving cloud-based TPUs (tensor processing units) in order to develop machine learning software. [7] [8] The TPU research cloud provides free access to a cluster of cloud TPUs to researchers engaged in open-source machine learning research. [9]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]